Affiliations: [a] School of Science, Nanjing University of Posts and Telecommunications, Nanjing, China
| [b] School of Business, Nanjing Normal University, Nanjing, China
| [c] School of Civil Engineering, Wuhan University, Wuhan, China
| [d] Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, Slovakia; Department of Algebra and Geometry, Faculty of Science, Palacký University, Czech Republic
| [e] Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia; Machine Intelligence Institute, Iona College, New Rochelle, NY, USA; Emeritus Professor of Information Systems Iona College, New Rochelle, NY, USA
Correspondence:
[*]
Corresponding author. LeSheng Jin, School of Business, Nanjing Normal University, Nanjing, China. E-mail: [email protected] and Zhen-Song Chen, School of Civil Engineering, Wuhan University, Wuhan, China. E-mail: [email protected].
Abstract: Interval basic uncertain information is a generalization of basic uncertain information. Due to their special structures, the induced aggregation and induced OWA operators have diversified inducing aggregation modes for them. In order to provide both normative paradigms and special ways to perform reasonable induced aggregation with vectors of interval basic uncertain information, this work systematically analyzes some substantial ways of performing induced aggregation by special means of non-induced aggregation. Numerous inducing posets are suggested to use which can help automatically generate weight vectors. Some special weights generation methods based on complex inducing information with numerical examples are also proposed and presented.
